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<table width="100%" summary="page for los"><tr><td>los</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2> Length of Stay Data </h2>

<h3>Description</h3>

<p>Length of stay for 201 patients that stayed at the University Hospital
of Lausanne during the year 2000.
</p>


<h3>Usage</h3>

<pre>data(los, package="robustbase")</pre>


<h3>Format</h3>

<p>Vector of integer values giving the length of stay (days):
</p>
<p>int [1:201] 16 13 17 4 15 24 59 18 33 8 ...
</p>


<h3>Details</h3>

<p>These data may be used to estimate and predict the total resource
consumption of this group of patients.
</p>
<p>Cf. Ruffieux, Paccaud and Marazzi (2000).
</p>


<h3>Source</h3>

<p>The data were kindly provided by A. Marazzi.
</p>
<p>Cf. Hubert, M. and Vandervieren, E. (2006), p. 13&ndash;15.
</p>


<h3>References</h3>

<p>Ruffieux, C., Paccaud, F. and A. Marazzi (2000)
Comparing rules for truncating hospital length of stay;
<em>Casemix Quarterly</em> <b>2</b>, n. 1.
</p>
<p>See also those for <code>adjbox</code>.
</p>


<h3>Examples</h3>

<pre>
 summary(los) # quite skewed, with median(.) = 8
 plot(table(los))
 boxplot(los, horizontal=TRUE, add=TRUE, col = "red", axes=FALSE)
 ##-&gt; "outliers" instead of "just skewed"

 hist(log(los))
 boxplot(log(los), add=TRUE, col=2, border=2, horizontal = TRUE, at = -1)

 ## Hubert and Vandervieren (2006), p. 15, Fig. 11.
 adjbox(los, col = "gray", staplecol="red", outcol = "red",
        main = "(Skewness-)Adjusted and original boxplot for 'los' data")
 boxplot(los, add = TRUE, staplewex= 0.2, outcex= 0.5, outpch= 4,
         staplecol = "blue", outcol = "blue", staplelwd=2)
 legend("topright", c("adjbox(los)", "boxplot(los)"),
        col=c("red","blue"), lwd = 1:2, bty="n")
</pre>


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